Focal plane arrays are used to digitally capture electromagnetic radiation, and are common components of digital imaging systems. A focal plane array comprises an array of individual detectors, generally photodiodes, which produce current when exposed to photons of sufficient energy. This current, later converted to a voltage, may be treated in a variety of ways to generate an image that is displayed to the end user.
Individual detectors in focal plane arrays are subject to non-uniformity errors. Specifically, if two detectors at a uniform temperature are exposed to the same scene information, their response voltages may differ. Non-uniformity errors are described in terms of offset (the difference in response to a calibrated input from the expected response) and gain (the difference in slope of the line between two responses to two calibrated inputs from the expected slope). These errors increase the minimum detectable signal, decrease the signal-to-noise ratio, and thus have a detrimental effect on system performance. The effect is particularly severe for high performance, high sensitivity detector arrays.
Various solutions to the problem of detector non-uniformity error have been developed. These solutions generally involve exposing the detector array to calibrated electromagnetic radiation. Under the assumption that all detectors should exhibit equal signals when exposed to an equal intensity of radiation, response deviations from the nominal signals are used to obtain offset and gain correction maps, which are then applied to detected signals before displaying the image data.
Perhaps the simplest way of obtaining correction maps is the two-point correction method, in which uniform radiation at two different precisely known temperatures is applied to the array and the response of each detector is measured. The offset and gain response of each detector is then calculated by approximating the response as a line through these two calibration points. For a given detector, the extrapolation of the line through any particular temperature gives the offset response of the detector, and the gain is just the slope of the response line.
Because the detectors are assumed to be linear devices, correcting detector gain and offset at one set of exposure intensity levels is assumed to allow correction at all other levels. However, detectors often do not respond linearly, resulting in errors even after correction by the two-point method. In one enhancement of the two-point method, detector response is measured at various temperatures to experimentally obtain offset and gain corrections for each detector over the range of expected operating temperatures. Because detector response typically changes non-linearly with temperature, measuring at various temperatures is commonly more accurate than the two-point correction method.
Commonly, focal plane array detectors are tested under controlled conditions after manufacture, for example using the two-point correction method, to derive an offset table and/or a gain table. Such tables might include, for example, the gain of each detector and the offset of the detector at one particular temperature, allowing the offset to be calculated at any other temperature for each detector in an array. These tables are fixed after testing and used to correct for each detector's unique non-uniformity error. However, because non-uniformity errors may be nonlinear and may vary over time and under different operating conditions, correction using data solely from calibration shortly after manufacture is error-prone. Thus, manufacturers have developed non-uniformity error correction methods that can be performed in the field.
For example, one proposal involves application of known electromagnetic radiation signals using shutters, mirrors, or the like to achieve a two-point calibration during operation. As in the two-point correction method performed described above, correction values are calculated for each detector in the array based on the assumption that all detectors should exhibit equal signals when exposed to an equal intensity of radiation. Because the in-field method may be performed repeatedly during operation, rather than once following manufacture, non-uniformity errors that evolve over time or in response to operating conditions may be corrected.
One specific in-field calibration approach has been to periodically place a mechanical paddle, designed to act as a uniform radiation source, in front of the detector array such that an image of the ideally uniform paddle surface is captured. Because the paddle is assumed to be uniform, deviations in individual detectors are treated as errors, from which a revised offset table may be derived. However, this particular approach has several drawbacks. First, scene acquisition must be interrupted, which is undesirable where continuously obtaining scene information is required or preferred. Second, because the paddle is treated as an ideal surface, actual non-uniformities in the reflectivity of the paddle will mistakenly be assumed to be detector non-uniformity error and “burned in” to the offset table. Furthermore, paddle systems correct detector response at only one electromagnetic frequency at a time, making it difficult or impossible to correct for errors that vary as a function of radiation wavelength or intensity.
Another general approach to non-uniformity error correction in focal plane arrays has been to image substantially identical scene information on a plurality of detectors within the array. By comparing the resultant output from a plurality of detectors exposed to substantially identical scene information, detector non-uniformity errors, which remain spatially fixed, may be identified and corrected. In this general method, scene information is translated across the focal plane array either passively, by comparing subsequent frames of a moving set of objects, or actively, by introducing mechanical motion such as dithering in the imaging system. Under either method, because scene information has been translated across the array, multiple detectors are assumed to have seen substantially identical scene information in subsequent frames. Thus, any differences between reported values are assumed to be due to detector non-uniformity errors, and may be used to derive the offset and gain correction tables.
For example, U.S. Pat. No. 6,507,018 describes a passive method of non-uniformity correction. In the passive method described by U.S. Pat. No. 6,507,018, a determination is first made whether sufficient relative motion exists between the scene and focal plane array. If so, the difference in temporal frequency between the high-frequency moving scene information and the low-frequency stationary detector non-uniformity errors may permit the two signals to be decoupled. Then, a spatial low pass filter algorithm is used to perform corrections to the high-temporal-frequency moving scene information. The algorithm estimates each detector's offset and gain value by comparing each detector's response to a local response average among neighboring detectors that are exposed to substantially identical scene information. This method may be performed iteratively, to update the offset and gain tables in response to changing conditions. However, one limitation to this method is that sufficient scene motion is required to separate scene information from detector non-uniformity error. To address this limitation, intentional motion such as mechanical dithering may be introduced.
An example of a prior art nonuniformity correction method involving mechanical dithering is described in U.S. Pat. No. 5,925,880. In the described method, periodic mechanical motion is introduced to the imaging system such that under the assumption of a slowly changing scene, multiple detectors are exposed to substantially identical scene information. As in the passive method, neighborhood averaging is used to determine the ideal output for each detector, and thus to derive updated gain and offset correction update tables. This method, however, suffers from several drawbacks. First, because the algorithm assumes a precise magnitude of scene translation across the detector, the method is very sensitive to dither translation accuracy. Second, any detector with a response substantially different from the ideal value will skew the average detector response of those detectors in its neighborhood. Furthermore, because the method assumes a slowly changing scene, performance can suffer during rapid scene movement. This potential decline in performance may be overcome to some extent by increasing the dithering frequency, but such an increase may come at the expense of dithering accuracy and mechanical reliability. Therefore, the mechanical dithering method is not particularly suitable for applications with rapid scene motion, such as moving platform applications.
Another nonuniformity correction method using mechanical dithering is described in U.S. Pat. No. 5,925,875. The described method entails passing the dithered image through a temporal high pass filter. Because dithering introduces known periodic motion to scene information, the high pass filter passes high temporal frequency scene information while removing low temporal frequency non-uniformity error. The image is then restored either by time-delay-integration (TDI) or by spatial inversion. In TDI, detectors imaging similar scene information in consecutive frames are matched, and their signals are time-averaged over several frames, from which the image may be restored. In spatial inversion, effects of dithering and filtering are reduced using precise knowledge of the dither pattern and high pass filter response, such that an image signal is constructed from the filtered signal.
Both of the methods disclosed in U.S. Pat. No. 5,925,875 suffer from several weaknesses. The temporal high pass filter algorithm requires storage and real-time access of several full image frames simultaneously. Because of the storage limitations of embedded memory technology, the application of this method to higher resolution images is limited. Second, the high pass filter will pass all high temporal frequency information, whether induced by dithering or by imaging platform motion. Deconvolution of these two sources of motion introduces severe complications in a moving platform application. Under the TDI technique, where detectors measuring similar scene information in consecutive frames are matched, the platform motion must be measured and compensated for in the detector matching process. Platform motion may be measured either with mechanical devices or additional image processing, but at a penalty of size, cost, and complexity. Under the spatial inversion technique, where the image signal is constructed using precise knowledge of the dither pattern and filter response to remove image distortion, the algorithm will need to take platform motion into account. As in the TDI case, precise knowledge of platform motion will be needed, at the penalty of size, cost, and complexity.
In light of the foregoing, there is a need for a relatively simple and robust method to provide non-uniformity error correction of detectors in a focal plane array, particularly in a high resolution imaging system and in a moving platform application.